Ghent University Academic Bibliography

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Machine learning-based urine peptidome analysis to predict and understand mechanisms of progression to kidney failure

Ziad A. Massy, Oriane Lambert, Marie Metzger, Mohammed Sedki, Adeline Chaubet, Benjamin Breuil, Acil Jaafar, Ivan Tack, Thao Nguyen-Khoa, Melinda Alves, et al.

(2023) KIDNEY INTERNATIONAL REPORTS. 8(3). p.544-555
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The urinary proteomics classifier chronic kidney disease 273 predicts cardiovascular outcome in patients with chronic kidney disease

Francis Verbeke (UGent) , Justyna Siwy, Wim Van Biesen (UGent) , Harald Mischak, Anneleen Pletinck, Eva Schepers (UGent) , Nathalie Neirynck (UGent) , Pedro Magalhães, Martin Pejchinovski, Claudia Pontillo, et al.

(2021) NEPHROLOGY DIALYSIS TRANSPLANTATION. 36(5). p.811-818
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Early detection of diabetic kidney disease by urinary proteomics and subsequent intervention with spironolactone to delay progression (PRIORITY): a prospective observational study and embedded randomised placebo-controlled trial

Nete Tofte, Morten Lindhardt, Katarina Adamova, Stephan J. L. Bakker, Joachim Beige, Joline W. J. Beulens, Andreas L. Birkenfeld, Gemma Currie, Christian Delles, Ingo Dimos, et al.

(2020) LANCET DIABETES & ENDOCRINOLOGY. 8(4). p.301-312
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Value of urinary proteome-based classifier associated with chronic kidney disease and its progression in the prognosis of a patient-relevant endpoint, mortality

Justyna Siwy, Pedro Magalhaes, Eva Schepers (UGent) , Claudia Pontillo, Antonia Vlahou, Griet Glorieux (UGent) and Harald Mischak

(2018) NEPHROLOGY DIALYSIS TRANSPLANTATION. 33(suppl. 1).
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A urinary proteome-based classifier for the early detection of decline in glomerular filtration

Claudia Pontillo, Lotte Jacobs, Jan A Staessen, Joost P Schanstra, Peter Rossing, Hiddo JL Heerspink, Justyna Siwy, William Mullen, Antonia Vlahou, Harald Mischak, et al.

(2017) NEPHROLOGY DIALYSIS TRANSPLANTATION. 32(9). p.1510-1516
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Noninvasive diagnosis of chronic kidney diseases using urinary proteome analysis

Justyna Siwy, Petra Zürbig, Angel Argiles, Joachim Beige, Marion Haubitz, Joachim Jankowski, Bruce A Julian, Peter G Linde, David Marx, Harald Mischak, et al.

(2017) NEPHROLOGY DIALYSIS TRANSPLANTATION. 32(12). p.2079-2089
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Diagnosis and prediction of CKD progression by assessment of urinary peptides

Joost P Schanstra, Petra Zürbig, Alaa Alkhalaf, Angel Argiles, Stephan JL Bakker, Joachim Beige, Henk JG Bilo, Christos Chatzikyrkou, Mohammed Dakna, Jesse Dawson, et al.

(2015) JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY. 26(8). p.1999-2010

Academic Bibliography

Machine learning-based urine peptidome analysis to predict and understand mechanisms of progression to kidney failure

The urinary proteomics classifier chronic kidney disease 273 predicts cardiovascular outcome in patients with chronic kidney disease

Early detection of diabetic kidney disease by urinary proteomics and subsequent intervention with spironolactone to delay progression (PRIORITY): a prospective observational study and embedded randomised placebo-controlled trial

Value of urinary proteome-based classifier associated with chronic kidney disease and its progression in the prognosis of a patient-relevant endpoint, mortality

A urinary proteome-based classifier for the early detection of decline in glomerular filtration

Noninvasive diagnosis of chronic kidney diseases using urinary proteome analysis

Diagnosis and prediction of CKD progression by assessment of urinary peptides

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